Adaptation of a constructive heuristic for the 3-D bin packing problem to the box lot constraint
Jeanmoye, Simon
Promotor(s) : Limbourg, Sabine
Date of defense : 24-Jun-2020/26-Jun-2020 • Permalink : http://hdl.handle.net/2268.2/8914
Details
Title : | Adaptation of a constructive heuristic for the 3-D bin packing problem to the box lot constraint |
Author : | Jeanmoye, Simon |
Date of defense : | 24-Jun-2020/26-Jun-2020 |
Advisor(s) : | Limbourg, Sabine |
Committee's member(s) : | Baratto, Marie
Paquay, Célia |
Language : | English |
Number of pages : | 78 |
Keywords : | [en] Packing [en] Heuristics [en] Air transportation [en] Extreme points [en] Box lot constraint |
Discipline(s) : | Business & economic sciences > Production, distribution & supply chain management |
Target public : | Researchers Professionals of domain Student |
Institution(s) : | Université de Liège, Liège, Belgique |
Degree: | Master en ingénieur de gestion, à finalité spécialisée en Supply Chain Management and Business Analytics |
Faculty: | Master thesis of the HEC-Ecole de gestion de l'Université de Liège |
Abstract
[en] This master thesis first provides a brief presentation of the air freight supply chain. The actors involved in air cargo as well as the existing information and physical flows along this chain are described. A particular focus is put on the outbound handling processes, i.e. the handling of goods from their arrival at the airport to their loading onto the cargo aircraft.
Then, the box lot constraint in the context of air transport is introduced. After a description of the constraint types associated with Container Loading Problems in the literature, the box lot constraint is defined and its existence when building Unit Load Devices in practice is justified.
Finally, the tailored two-phase constructive heuristic presented in Paquay, Limbourg, & Schyns (2018) which aims to solve the three-dimensional Multiple Bin Size Bin Packing Problem with transportation constraints, is extended in order to take into account the box lot constraint. Following a description of the proposed heuristic adaptation, computational experiments are carried out to assess the general heuristic performance and to determine the box lots impact on both the computational time and the solution quality. The proposed approach turns out to be promising since it achieves filling rates close to the original formulation of the problem, while remaining very fast.
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